code: def make_voting_classifier() -> Callable[..., VotingClassifier]:
      """
      Parameters
      ----------
      X: Optional[SUPPORTED_FEAT_TYPES] = None
          The X data to fit models on, if None, no fitting occurs
  
      y: Optional[SUPPORTED_FEAT_TYPES] = None
          The y data to fit models on, if None, no fitting occurs
  
      models: Optional[Collection[AutoSklearnClassificationAlgorithm]] = None
          Any collection of algorithms to use, if None, DummyClassifiers are used
      """
  
      def _make(
          X: Optional[SUPPORTED_FEAT_TYPES] = None,
          y: Optional[SUPPORTED_TARGET_TYPES] = None,
          models: Optional[
              Collection[AutoSklearnClassificationAlgorithm]
          ] = None,
          seed: Union[int, None, np.random.RandomState] = DEFAULT_SEED,
      ) -> VotingClassifier:
          assert not (X is None) ^ (y is None)
          if not models:
              validator = InputValidator(is_classification=True).fit(
                  X, y
              )
              models = [
                  MyDummyClassifier(
                      feat_type=validator.feature_validator.feat_type,
                      config=1,
                      random_state=seed,
                  )
                  for _ in range(5)
              ]
  
          if X is not None:
              for model in models:
                  model.fit(X, y)
  
          voter = VotingClassifier(estimators=None, voting="soft")
          voter.estimators_ = models
          return voter
  
      return _make
  
file_path: auto-sklearn/test/fixtures/ensembles.py
imports: from __future__ import annotations
  from typing import Callable, Collection, Optional, Union
  import numpy
  from sklearn.ensemble import VotingClassifier, VotingRegressor
  from autosklearn.data.validation import SUPPORTED_FEAT_TYPES, SUPPORTED_TARGET_TYPES, InputValidator
  from autosklearn.evaluation.abstract_evaluator import MyDummyClassifier, MyDummyRegressor
  from autosklearn.pipeline.components.base import AutoSklearnClassificationAlgorithm, AutoSklearnRegressionAlgorithm
  from pytest_cases import fixture
  from test.conftest import DEFAULT_SEED
label_desc: Use image node_id 1 for calling a global function with example usage: make_voting_classifier() and returns: _make, voter